Theoretical analysis demonstrates improved circuit lower bounds for constant-depth GCC0(k) circuits, highlighting stronger parameter scaling within the algorithmic method.
We give a randomness-efficient probabilistic replacement for G(k) gates and derive an improved quantitative circuit lower-bound consequence for constant-depth GCC^0(k) circuits within the Williams algorithmic-method framework. For a G(k) gate of fan-in m and pointwise error ε, the construction usesO(klog m+log(1/ε))random bits and yields a constant-depth modular/AND representation whose logarithmic size and AND fan-in are bounded byO\!((klog m+log(1/ε))log(1/ε)). At CircuitSAT scale, writing L=log s, the resulting circuit-level parameters are total randomness O(kL) and logarithmic size and AND fan-in O(kL^2). Combining these parameters with the Grewal–Kumar/Williams SAT-to-lower-bound framework yields, for fixed circuit depth and admissible parameters, a lower-bound exponentΛ(n,k)=min\{{n3η/F}{k},{n2η/F}{√k}\},where 1/2<η<1 and F=f(2d+O(1)) is the depth-dependent exponent arising in the symmetric-circuit conversion. Consequently, there exists a language in ENP requiring nonuniform depth-d GCC^0(k) circuits of sizeexp(Ω(Λ(n,k))). On the common range of applicability, and when the same normalized depth-bound function is used, this improves the quantitative k-dependence obtained from the Grewal–Kumar algorithmic-method lower bound. The result is intentionally scoped to this circuit-complexity framework. It does not establish a lossless lifting of the full ACC^0 lower bound to GCC^0(k), and it does not resolve P versus NP.
No takes yet. Share an insight, caveat, or question.
Qasim Shirazi (2026) studied this question.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: